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Brain Perfusion Imaging - Performance and Accuracy

NeSC Research Seminar Series
Fan Zhu

I aim to use computer science methodologies to solve brain perfusion imaging (medical imaging) problems in my PhD research.
I focus on three issues. The first issue addressed was the acceleration of the algorithms used to generate hemodynamic maps. It proved possible, using GPGPUs, to achieve substantial speedups while retaining the quality of generated hemodynamic maps. The next two investigations sought to make better use of the information latent in the time-domain of CT perfusion scans. The first of these showed that Gaussian process regression (GPR) could significantly enhance the quality of derived data at modest computational cost. The second of these then used that denoised data to improve the discrimination between healthy, penumbra and dead tissue.

Date and time: 
Friday, 12 October, 2012 - 10:30
90 minutes
Turing Room (5.42), Informatics Forum